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Explicit model predictive control through robust optimization

Pappas Iosif, Diangelakis Nikolaos, Pistikopoulos Stratos

Πλήρης Εγγραφή


URI: http://purl.tuc.gr/dl/dias/7E883FC5-F99D-40A3-AA63-998594436597
Έτος 2023
Τύπος Δημοσίευση σε Περιοδικό με Κριτές
Άδεια Χρήσης
Λεπτομέρειες
Βιβλιογραφική Αναφορά I. Pappas, N. A. Diangelakis and E. N. Pistikopoulos, “Explicit model predictive control through robust optimization,” AIChE J., vol. 69, no. 10, Oct. 2023, doi: 10.1002/aic.18172. https://doi.org/10.1002/aic.18172
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Περίληψη

A strategy that calculates an explicit state feedback policy to regulate constrained uncertain discrete-time uncertain linear systems is presented. We consider uncertain processes, affected by box-bounded multiplicative uncertainty as well as bounded additive uncertainty with linear state and inputs constraints. The proposed method includes (i) the calculation of a terminal set constraint and (ii) the robust reformulation of state constraints in the prediction horizon. These features allow the derivation of the desired policy by solving a single multiparametric quadratic programming problem that guarantees feasible operation in the presence of uncertainty. Additionally, we employ variable and constraint elimination approaches to enhance the computational performance of the strategy. We demonstrate the steps and benefits of these developments with a numerical example and a chemical engineering case study.

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